Cardiac Abnormalities Classification Model Using Improved Deep Learning Approach

Arishi A.; Kanjramnilkunathil S.A.; Rajan S.K.; Kausar A.; Arjumand A.; Torres-Cruz F. · International Journal of Intelligent Systems and Applications in Engineering (2024)

Resumen

Worldwide, deep learning (DL) is applied in the healthcare industry. In the medical data set, DL approaches aid in the prevention of cardiac illnesses and locomotor disorders. The finding of such crucial information gives researchers important new knowledge on how to apply their diagnosis as well as therapy to a specific patient. Researchers analyze vast quantities of intricate healthcare data using a variety of DL techniques, which enable medical experts to forecast disorders. The primary motivation for developing a model that identify cardiac disorders, which will help lots of people around the world. This paper offerings a model for detecting cardiac diseases. The model is made by improving the Convolutional Neural Network (CNN) termed as Custom CNN (C-CNN). The new results depict that the proposed model works better. The proposed measure of heart disease categorization performs better when compared to certain previously published approaches.

Instituciones: Universidad Nacional del Altiplano